Though spillovers have been initially described in the Multiple Streams Framework (MSF), we know little about how to conceptualize and measure them. To investigate spillovers, we draw on the case of fur farming bans during the COVID‐19 pandemic. Whereas fur farming has long been criticized for its animal welfare problems, with the onset of the pandemic, it turned into a public health issue. We argue that COVID‐19 outbreaks on fur farms can be characterized as spillovers from the health to the agricultural sector, opening a window of opportunity for policy change. By means of a quantitative analysis, we explore under which conditions policy change in fur farming took place. By this, our study also presents an innovative attempt to quantitatively apply the MSF. We use Cox proportional hazard models based on data from 2017 to 2022 to study the effect of MSF variables on policy change for all countries that documented outbreaks on fur farms. The empirical results demonstrate the relevance of integrating spillovers into the MSF. The study makes theoretical contributions by conceptualizing spillovers and methodical contributions by offering a novel and quantitative approach to the MSF.
Parth et al. (Fri,) studied this question.